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Abstract
It is often asserted that stock splits and stock dividends are purely cosmetic events.
However, many studies have documented several stock market effects associated with
stock splits and stock dividends. This paper examines the effects of these two types
of events for the Danish stock market. Consistent with the existing literature, the
two events are associated with a significantly positive announcement effect of ap-
proximately 2.5%. However, when examining the two events more carefully, several
important results are obtained. First, a firm's motivation for announcing the two
events is completely different. Second, the positive stock market reaction is closely
related to associated changes in a firm's payout policy, but the relationship varies for
the two types of events. Finally, there is only very weak evidence for a change in the
liquidity of the stock. On the whole, after controlling for the firm's payout policy,
the results suggest that a stock split is a cosmetic event and that a stock dividend
on its own is considered negative news.
Key words: Stock splits; Stock dividends; Cash dividends; Signaling; Liquidity

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Rational expectations models make stringent assumptions on the agent's
knowledge about the true model. This paper introduces a model in which the
rational agent realizes that using a given model involves approximation errors,
and adjusts behavior accordingly. If the researcher accounts for this empirical
rationality on part of the agent, the resulting empirical model assigns
likelihood to the data actually observed, unlike in the unmodified rational expectations
case. A Lucas (1978)-type asset pricing model which incorporates
empirical rationality is constructed and estimated using U.S. stock data. The
equilibrium asset pricing function is seriously affected by the existence of approximation
errors and the descriptive properties and normative implications
of the model are significantly improved. This suggests that investors do not
| and should not | ignore approximation errors.
Keywords: Approximation errors, model uncertainty, estimation of structural
models, rational expectations, asset pricing.